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cs.LG2023★ 2 cited
Eigensubspace of Temporal-Difference Dynamics and How It Improves Value Approximation in Reinforcement Learning
Qiang He, Tianyi Zhou, Meng Fang +1
We propose a novel value approximation method, namely Eigensubspace Regularized Critic (ERC) for deep reinforcement learning (RL). ERC is motivated by an analysis of the dynamics o…
cs.LG2023★ 2 cited
Interpretable Reward Redistribution in Reinforcement Learning: A Causal Approach
Yudi Zhang, Yali Du, Biwei Huang +4
A major challenge in reinforcement learning is to determine which state-action pairs are responsible for future rewards that are delayed. Reward redistribution serves as a solution…